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Linear Programming Using MATLAB® / by Nikolaos Ploskas, Nikolaos Samaras
(Springer Optimization and Its Applications. ISSN:19316836 ; 127)
版 | 1st ed. 2017. |
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出版者 | (Cham : Springer International Publishing : Imprint: Springer) |
出版年 | 2017 |
本文言語 | 英語 |
大きさ | XVII, 637 p. 59 illus., 47 illus. in color : online resource |
著者標目 | *Ploskas, Nikolaos author Samaras, Nikolaos author SpringerLink (Online service) |
件 名 | LCSH:Mathematical optimization LCSH:Computer software LCSH:Computer science -- Mathematics 全ての件名で検索 LCSH:Algorithms FREE:Continuous Optimization FREE:Mathematical Software FREE:Mathematical Applications in Computer Science FREE:Algorithms |
一般注記 | 1. Introduction -- 2. Linear Programming Algorithms -- 3. Linear Programming Benchmark and Random Problems -- 4. Presolve Methods -- 5. Scaling Techniques -- 6. Pivoting Rules -- 7. Basis Inverse and Update Methods -- 8. Revised Primal Simplex Algorithm -- 9. Exterior Point Simplex Algorithms -- 10. Interior Point Method -- 11. Sensitivity Analysis -- Appendix: MATLAB’s Optimization Toolbox Algorithms -- Appendix: State-of-the-art Linear Programming Solvers;CLP and CPLEX This book offers a theoretical and computational presentation of a variety of linear programming algorithms and methods with an emphasis on the revised simplex method and its components. A theoretical background and mathematical formulation is included for each algorithm as well as comprehensive numerical examples and corresponding MATLAB® code. The MATLAB® implementations presented in this book are sophisticated and allow users to find solutions to large-scale benchmark linear programs. Each algorithm is followed by a computational study on benchmark problems that analyze the computational behavior of the presented algorithms. As a solid companion to existing algorithmic-specific literature, this book will be useful to researchers, scientists, mathematical programmers, and students with a basic knowledge of linear algebra and calculus. The clear presentation enables the reader to understand and utilize all components of simplex-type methods, such as presolve techniques, scaling techniques, pivoting rules, basis update methods, and sensitivity analysis HTTP:URL=https://doi.org/10.1007/978-3-319-65919-0 |
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電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
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電子ブック | オンライン | 電子ブック |
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Springer eBooks | 9783319659190 |
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EB00228730 |
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データ種別 | 電子ブック |
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分 類 | LCC:QA402.5-402.6 DC23:519.6 |
書誌ID | 4000115408 |
ISBN | 9783319659190 |
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※2017年9月4日以降